Companies may need to ensure the accuracy and consistency of financial data stored in enterprise databases. Examples of such databases may include Human Resource (“HR”) payroll, payroll posting, General Ledger (“CG/L”) accounts, tax, and travel management. Two databases may be logically related when a data field in a first database is logically related to a data field in a second database. A first data field is logically related to a second data field when the data recorded in the first and the second data field may be traced to a common original event. Examples of common original events may include monthly salary payment to an employee and associated payroll deductions, an expense debit for a group of employees, or an employee's travel expense and reimbursement for a month. In another example, after the travel expense reimbursement for an employees' business trip was processed, the controller of the corporation may receive an overview of the amount that was paid out in comparison to the amount that was requested to be reimbursed. In such a situation, the first data field may include the amount that the employee requested to be reimbursed and the second data field may include the amount actually reimbursed to the employee, where the business trip is the common original event for both data fields, and therefore, they are logically related. When data are recorded in logically related databases, the data may have discrepancies for a number of reasons. For example, monthly payroll data for an employee may differ from corresponding monthly payroll posting data in finance accounting because the data for the employee may not be posted to the payroll accounting at the time of comparison due to off days. In another example, data in a tax database may differ from corresponding data in a payroll posting database with respect to a tax code due to lack of coordination between the two databases. Companies may need to report and explain any discrepancies among logically related databases to internal and external authorities by regulation or by law.
Currently, there is no standard tool to automatically reconcile and report discrepancies in logically related databases. Instead, individual software applications generate tables of data in separate reports. As a result, to reconcile databases, these reports are compared manually by human resource or accounting experts, a process that is time consuming and prone to human errors.
Current HR management systems in marketplace do not have the capability of reconciling diverse databases in an enterprise business information system. There is a great need for system and method that automate the database reconciliation process.